This paper examines the hypothesis that wage discrimination emerged at the beginning of the twentieth century. I test for wage discrimination by estimating the female-male productivity ratio from samples of manufacturing firms in the northeast, and then comparing the estimated productivity ratio to the wage ratio. I find that women did not face wage discrimination in manufacturing during the nineteenth century. In 1900 there was wage discrimination against women in white-collar jobs, but not in blue-collar jobs. Wage discrimination persisted, and in 2002 the female-male wage ratio was less than the productivity ratio.
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Testing for Wage Discrimination in U.S. Manufacturing
September 2012
Working Paper Number:
CES-12-23
In spite of the large literature on labor market discrimination, the quantity of solid evidence on discrimination is relatively limited. This is because evidence of discrimination is difficult to obtain. Two individuals may be treated equally, but this does not prove discrimination unless we can show that the differences in treatment were not justified by differences in productivity. The method most commonly used to identify wage discrimination, the Oaxaca decomposition, is flawed because any omitted variables that are correlated with gender will contribute to the unexplained portion of the wage gap, leading to an over- or under-estimation of wage discrimination. Audit studies provide more direct evidence of differential treatment, but are costly to carry out. Only a small number of studies attempt to measure worker productivity to see if wage differences are justified. This may be because the data needed to measure productivity are difficult to obtain. This paper tests for wage discrimination by gender and race by estimating relative productivity from 2002 Census of Manufacturing data linked to demographic information on workers from Longitudinal Employer-Household Dynamics (LEHD) files. Comparing the estimated productivity ratios to the observed wage ratios, I conclude that females and blacks face wage discrimination in US manufacturing.
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Production Function and Wage Equation Estimation with Heterogenous Labor: Evidence from a New Matched Employer-Employee Dataset
April 2004
Working Paper Number:
CES-04-05
In this paper, we first describe the 1990 DEED, the most recently constructed matched employeremployee data set for the United States that contains detailed demographic information on workers (most notably, information on education). We then use the data from manufacturing establishments in the 1990 DEED to update and expand on previous findings, using a more limited data set, regarding the measurement of the labor input and theories of wage determination (Hellerstein, et al., 1999). We find that the productivity of women is less than that of men, but not by enough to fully explain the gap in wages, a result that is consistent with wage discrimination against women. In contrast, we find no evidence of wage discrimination against blacks. We estimate that both the wage and productivity profiles are rising but concave to the origin (consistent with profiles quadratic in age), but the estimated relative wage profile is steeper than the relative productivity profile, consistent with models of deferred wages. We find a productivity premium for marriage equal to that of the wage premium, and a productivity premium for education that somewhat exceeds the wage premium. Exploring the sensitivity of these results, we also find that different specifications of production functions do not have any qualitative effects on the these results. Finally, the results indicate that the returns to productive inputs (capital, materials, labor quality) as well as the residual variance are virtually unaffected by the choice of the construction of the labor quality input.
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Further Evidence from Census 2000 About Earnings by Detailed Occupation for Men and Women: The Role of Race and Hispanic Origin
November 2011
Working Paper Number:
CES-11-37
A 2004 report by the author reviewed data from Census 2000 and concluded "There is a substantial gap in median earnings between men and women that is unexplained, even after controlling for work experience (to the extent it can be represented by age and presence of children), education, and occupation." This paper extends the analysis and concludes that once those characteristics are controlled for, no further explanatory power is attributable to race or Hispanic origin.
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An Evaluation of the Gender Wage Gap Using Linked Survey and Administrative Data
November 2020
Working Paper Number:
CES-20-34
The narrowing of the gender wage gap has slowed in recent decades. However, current estimates show that, among full-time year-round workers, women earn approximately 18 to 20 percent less than men at the median. Women's human capital and labor force characteristics that drive wages increasingly resemble men's, so remaining differences in these characteristics explain less of the gender wage gap now than in the past. As these factors wane in importance, studies show that others like occupational and industrial segregation explain larger portions of the gender wage gap. However, a major limitation of these studies is that the large datasets required to analyze occupation and industry effectively lack measures of labor force experience. This study combines survey and administrative data to analyze and improve estimates of the gender wage gap within detailed occupations, while also accounting for gender differences in work experience. We find a gender wage gap of 18 percent among full-time, year-round workers across 316 detailed occupation categories. We show the wage gap varies significantly by occupation: while wages are at parity in some occupations, gaps are as large as 45 percent in others. More competitive and hazardous occupations, occupations that reward longer hours of work, and those that have a larger proportion of women workers have larger gender wage gaps. The models explain less of the wage gap in occupations with these attributes. Occupational characteristics shape the conditions under which men and women work and we show these characteristics can make for environments that are more or less conducive to gender parity in earnings.
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Hires and Separations in Equilibrium
January 2016
Working Paper Number:
CES-16-57
Hiring occurs primarily to fill vacant slots that occur when workers separate. Equivalently, separation occurs to move workers to better alternatives. A model of efficient separations yields several specific predictions. Labor market churn is most likely when mean wages are low and the variance in wages is high. Additionally, over the business cycle, churn decreases during recessions, with hires falling at the beginning of recessions and separations declining later to match hiring. Furthermore, the young disproportionately bear the brunt of employment declines. More generally, hires and separations are positively correlated over time as well as across industry and firm. These predictions are borne out in the LEHD microdata at the economy and firm level.
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Do Alternative Opportunities Matter? The Role of Female Labor Markets in the Decline of Teacher Quality
July 2006
Working Paper Number:
CES-06-22
This paper documents the widely perceived but little investigated notion that teachers today are less qualified than they once were. Using standardized test scores, undergraduate institution selectivity, and positive assortative mating characteristics as measures of quality, evidence of a marked decline in the quality of young women going into teaching between 1960 and 1990 is presented. In contrast, the quality of young women becoming professionals increased. The Roy model of selfselection is used to highlight how occupation differences in the returns to skill determine average teacher quality. Estimates suggest the significance of increasing professional opportunities for women in affecting the decline in teacher quality.
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Is There Really an Export Wage Premium? A Case Study of Los Angeles Using Matched Employee-Employer Data
February 2006
Working Paper Number:
CES-06-06
This paper investigates the effects of exporting on wages, specifically the claim that workers are paid higher wages if they are employed in manufacturing plants that export vis-'-vis plants that do not export. Past research on US plants has supported the existence of an export wage premium, though European studies dispute those results calling for more care in econometric investigation to control for worker characteristics. We answer this call developing a matched employee-employer data set linking worker characteristics from the one-in-six long form of the Decennial Household Census to manufacturing establishment data from the Longitudinal Research Database. Analysis focuses on 1990 and 2000 data for the Los Angeles Consolidated Metropolitan Statistical Area. Our results confirm that the average wage in manufacturing plants that export is greater than that in manufacturing plants that do not export. However, after controlling for worker characteristics such as age, gender, education, race and nationality, the export wage premium vanishes. That is, when comparing workers with similar characteristics, there is no wage difference between exporting and non-exporting plants. These results concord with recent findings from Europe and elsewhere.
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The Influence Of Location On Productivity: Manufacturing Technology In Rural And Urban Areas
December 1991
Working Paper Number:
CES-91-10
Policies to counter the growing discrepancy between economic opportunities in rural and urban areas have focused predominantly on expanding manufacturing in rural areas. Fundamental to the design of these strategies are the relative costs of production and productivity of manufacturing in rural and urban areas. This study aims to develop information that can be used to assess the productivity of manufacturing in rural and urban areas. Production functions are estimated in the meat products and household furniture industries to investigate selected aspects of the effect of rural, small urban, and metropolitan location on productivity. The results show that the effect of location on productivity varies with industry, size, and the timing of the entry of the establishment into the industry. While the analysis is specific to two industries, it suggests that development policies targeting manufacturing can be made more effective by focusing on industries and plants with characteristics that predispose them to the locations being supported.
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The Rural-Urban Gap In Manufacturing Productivity And Wages: Effects Of Industry Mix And Region
June 1997
Working Paper Number:
CES-97-06
This study analyzes urban and rural values of value added per worker and production worker wages tabulated from unpublished 1992 Census of Manufactures data. A decomposition of regional averages separates out effects of regional industry mix from within-industry differentials over a rural-urban continuum and for metro and nonmetro portions of census regions. Comparison of actual 1991-1993 employment growth with regional wage and productivity differentials shows that low wages are strongly associated with job growth.
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Technology Use and Worker Outcomes: Direct Evidence from Linked Employee-Employer Data
August 2000
Working Paper Number:
CES-00-13
We investigate the impact of technology adoption on workers' wages and mobility in U.S. manufacturing plants by constructing and exploiting a unique Linked Employee-Employer data set containing longitudinal worker and plant information. We first examine the effect of technology use on wage determination, and find that technology adoption does not have a significant effect on high-skill workers, but negatively affects the earnings of low-skill workers after controlling for worker-plant fixed effects. This result seems to support the skill-biased technological change hypothesis. We next explore the impact of technology use on worker mobility, and find that mobility rates are higher in high-technology plants, and that high-skill workers are more mobile than their low and medium-skill counterparts. However, our technology-skill interaction term indicates that as the number of adopted technologies increases, the probability of exit of skilled workers decreases while that of unskilled workers increases.
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